We present a general approach for designing approximation algorithms for a fundamental class of geometric clustering problems in arbitrary dimensions. More specifically, our appro...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
Clustering is an important problem and has numerous applications. In this paper we consider an important clustering problem, called the k-center problem. We are given a discrete p...
Abstract. The NP-complete Distinguishing Substring Selection problem (DSSS for short) asks, given a set of “good” strings and a set of “bad” strings, for a solution string ...
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...